Sold by: RocketMLÂ
Overview
Text region detector automatically detects the presence of text in natural scene images. Detecting text in constrained, controlled environments can typically be accomplished by using heuristic-based approaches. Natural scene text detection is different — and much more challenging. This model overcomes challenges related to Natural scene text detection like Image/sensor noise, Viewing angles, Blurring, Lighting conditions, Resolution, Non-paper objects, Non-planar objects, Unknown layout.
Highlights
- Natural scene text detection has challenges like Image/sensor noise, Viewing angles, Blurring, Lighting conditions, Resolution, Non-paper objects, Non-planar objects, Unknown layout. This model does a descent job.
Details
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Delivery method
Latest version
Deployed on AWS
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Dimension | Description | Cost/host/hour |
|---|---|---|
ml.c5.xlarge Inference (Batch) Recommended | Model inference on the ml.c5.xlarge instance type, batch mode | $0.10 |
ml.c5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.c5.xlarge instance type, real-time mode | $0.10 |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
Email support@rocketml.net for any questions or support
Additional details
Inputs
- Summary
See example notebook for example usage.
- Input MIME type
- application/x-image
See Input Summary
See Input Summary
Resources
Vendor resources
Support
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Customer reviews
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1 external reviews
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Saswat M.
A great tool for text recognition in natural scene images
Reviewed on Nov 16, 2023
Review provided by G2
What do you like best about the product?
Text region detector automatically detects the presence of text in natural scene images. Detecting text in constrained, controlled environments can typically be accomplished by using heuristic-based approach.
What do you dislike about the product?
The UI can be worked upon to make it more user friendly
What problems is the product solving and how is that benefiting you?
This model overcomes challenges related to Natural scene text detection like Image/sensor noise, Viewing angles, Blurring, Lighting conditions, Resolution, Non-paper objects, Non-planar objects, Unknown layout.